Evaluating sarcopenia in emergency department triage: implications for hospitalization and critical care
Bibliographic record
Abstract
Background: Sarcopenia, characterized by age-related declines in skeletal muscle mass, strength, and physical performance, is common in older adults yet remains under-recognized in emergency medical settings. Despite its strong association with frailty and adverse clinical outcomes, sarcopenia is not routinely assessed in emergency department (ED) triage. This study aimed to determine the prevalence of possible sarcopenia among elderly adults presenting to the ED and evaluate its association with hospital admission and length of stay (LOS). Methods: A prospective cohort study was conducted in a tertiary urban ED in Taiwan between December 2020 and April 2021. Patients aged ≥65 years were consecutively enrolled and assessed for possible sarcopenia. Frailty was evaluated using the Edmonton Frail Scale and the Eastern Cooperative Oncology Group performance status. The primary outcomes included ED disposition (hospital admission versus discharge) and unfavorable discharge outcomes. Secondary outcomes comprised hospital LOS and National Health Insurance (NHI) reimbursement points. Linear regression and multivariable logistic analyses were conducted, along with receiver operating characteristic (ROC) analysis. Results: Of the 890 patients enrolled, 481 (54.0%) were sarcopenic and were significantly older, had lower body weight, and exhibited higher frailty scores (p < 0.001). Sarcopenia was associated with higher rates of hospital admission (p < 0.001) and prolonged LOS (p < 0.001). After adjustment, sarcopenia independently predicted hospital admission (adjusted odds ratio (aOR) 1.39; 95% Confidence Interval (CI), 1.04–1.87) and extended LOS (aOR 3.29; 95% CI, 1.78–4.80). ROC analysis demonstrated moderate predictive capability (Area Under the Curve (AUC) = 0.706). Additionally, NHI reimbursement points and unfavorable discharge outcomes were significantly associated with sarcopenia. Conclusions: Sarcopenia is both prevalent and independently associated with adverse clinical outcomes among elderly adults in the ED. Incorporating sarcopenia assessment into triage protocols may improve early risk stratification and support more informed clinical decision-making in this population. Clinical Trial Registration: NCT04862936, retrospectively registered.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".